
<h1><span class="yiyi-st" id="yiyi-12">numpy.arctanh</span></h1>
        <blockquote>
        <p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.arctanh.html">https://docs.scipy.org/doc/numpy/reference/generated/numpy.arctanh.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
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<dt id="numpy.arctanh"><span class="yiyi-st" id="yiyi-13"> <code class="descclassname">numpy.</code><code class="descname">arctanh</code><span class="sig-paren">(</span><em>x</em><span class="optional">[</span>, <em>out</em><span class="optional">]</span><span class="sig-paren">)</span><em class="property"> = &lt;ufunc &apos;arctanh&apos;&gt;</em></span></dt>
<dd><p><span class="yiyi-st" id="yiyi-14">逆双曲正切元素。</span></p>
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<tr class="field-odd field"><th class="field-name"><span class="yiyi-st" id="yiyi-15">参数：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-16"><strong>x</strong>：array_like</span></p>
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<div><p><span class="yiyi-st" id="yiyi-17">输入数组。</span></p>
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<tr class="field-even field"><th class="field-name"><span class="yiyi-st" id="yiyi-18">返回：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-19"><strong>out</strong>：ndarray</span></p>
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<div><p><span class="yiyi-st" id="yiyi-20">数组的形状与<em class="xref py py-obj">x</em>相同。</span></p>
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<div class="admonition seealso">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-21">也可以看看</span></p>
<p class="last"><span class="yiyi-st" id="yiyi-22"><code class="xref py py-obj docutils literal"><span class="pre">emath.arctanh</span></code></span></p>
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<p class="rubric"><span class="yiyi-st" id="yiyi-23">笔记</span></p>
<p><span class="yiyi-st" id="yiyi-24"><a class="reference internal" href="#numpy.arctanh" title="numpy.arctanh"><code class="xref py py-obj docutils literal"><span class="pre">arctanh</span></code></a>是多值函数：对于每个<em class="xref py py-obj">x</em>，存在无限多个数字<em class="xref py py-obj">z</em>，使得<em class="xref py py-obj">tanh（z）= x  t5 &gt;。</em></span><span class="yiyi-st" id="yiyi-25">约定是返回其虚部在<em class="xref py py-obj">[ -  pi / 2，pi / 2]</em>中的<em class="xref py py-obj">z</em>。</span></p>
<p><span class="yiyi-st" id="yiyi-26">对于实值输入数据类型，<a class="reference internal" href="#numpy.arctanh" title="numpy.arctanh"><code class="xref py py-obj docutils literal"><span class="pre">arctanh</span></code></a>始终返回实际输出。</span><span class="yiyi-st" id="yiyi-27">对于不能表示为实数或无穷大的每个值，它会产生<code class="docutils literal"><span class="pre">nan</span></code>并设置<em class="xref py py-obj">无效</em>浮点错误标志。</span></p>
<p><span class="yiyi-st" id="yiyi-28">对于复值输入，<a class="reference internal" href="#numpy.arctanh" title="numpy.arctanh"><code class="xref py py-obj docutils literal"><span class="pre">arctanh</span></code></a>是具有分支切口<em class="xref py py-obj">[ -  1，-inf]</em>和<em class="xref py py-obj">[1，inf]</em>的复杂分析函数，并且在前者上从上方连续，在后者上从下方连续。</span></p>
<p><span class="yiyi-st" id="yiyi-29">反双曲正切也称为<em class="xref py py-obj">atanh</em>或<code class="docutils literal"><span class="pre">tanh^-1</span></code>。</span></p>
<p class="rubric"><span class="yiyi-st" id="yiyi-30">参考文献</span></p>
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<tr><td class="label"><span class="yiyi-st" id="yiyi-31"><a class="fn-backref" href="#id1">[R7]</a></span></td><td><span class="yiyi-st" id="yiyi-32">Abramowitz和I.A.</span><span class="yiyi-st" id="yiyi-33">Stegun，“Handbook of Mathematical Functions”，10th printing，1964，pp。</span><span class="yiyi-st" id="yiyi-34"><a class="reference external" href="http://www.math.sfu.ca/~cbm/aands/">http://www.math.sfu.ca/~cbm/aands/</a></span></td></tr>
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<tr><td class="label"><span class="yiyi-st" id="yiyi-35"><a class="fn-backref" href="#id2">[R8]</a></span></td><td><span class="yiyi-st" id="yiyi-36">维基百科，“反双曲函数”，<a class="reference external" href="http://en.wikipedia.org/wiki/Arctanh">http://en.wikipedia.org/wiki/Arctanh</a></span></td></tr>
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<p class="rubric"><span class="yiyi-st" id="yiyi-37">例子</span></p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">arctanh</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.5</span><span class="p">])</span>
<span class="go">array([ 0.        , -0.54930614])</span>
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